云南高校图书馆联盟文献共享服务平台- NEURAL

NEURAL_NETWORKS: 作品数：993被引量：1769H指数：16; 导出分析报告; 相关作者：李爱群费树岷宋爱国王一清温秀兰更多>>; 相关机构：东南大学南京航空航天大学北京理工大学中国石油大学（北京）更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家重点基础研究发展计划国家高技术研究发展计划中国博士后科学基金更多>>

Soft-GNN:towards robust graph neural networks via self-adaptive data utilization: 《Frontiers of Computer Science》2025年第4期1-12,共12页Yao WU Hong HUANG Yu SONG Hai JIN; supported by the National Natural Science Foundation of China(Grant No.62127808).; Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high performance.However,a major concern is their robustness,particularly when faced with g...; 关键词：graph neural networks node classification label noise robustness

Accelerating constraint-based neural network repairs by example prioritization and selection: 《Frontiers of Computer Science》2025年第4期125-127,共3页Long ZHANG Shuo SUN Jun YAN Jian ZHANG Jiangzhao WU Jian LIU; supported by the National Natural Science Foundation of China(Grant No.62132020);the Major Project of ISCAS(ISCAS-ZD-202302).; 1 Introduction Compared with retraining,fine-tuning,and other traditional approaches,neural network repair approaches[1-7]can significantly improve the robustness of neural networks with lower time and computing cost....; 关键词：REPAIRS constraint based parameter matrix neural networks repair techniques repaired neural network accelerating neural network

Predicting outcomes using neural networks in the intensive care unit: 《World Journal of Clinical Cases》2025年第11期1-11,共11页Gumpeny R Sridhar Venkat Yarabati Lakshmi Gumpeny; Patients in intensive care units(ICUs)require rapid critical decision making.Modern ICUs are data rich,where information streams from diverse sources.Machine learning(ML)and neural networks(NN)can leverage the rich da...; 关键词：Large language models HALLUCINATIONS Supervised learning Unsupervised learning Convoluted neural networks BLACK-BOX WORKFLOW

DAFFnet:Seed classification of soybean variety based on dual attention feature fusion networks: 《The Crop Journal》2025年第2期619-629,共11页Lingyu Zhang Laijun Sun Xiuliang Jin Xiangguang Zhao Shujia Li; supported by Natural Science Foundation of Heilongjiang Province of China(SS2021C005);Province Key Research and Development Program of Heilongjiang Province of China(GZ20220121);the Agricultural Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences.; Rapid,accurate seed classification of soybean varieties is needed for product quality control.We describe a hyperspectral image-based deep-learning model called Dual Attention Feature Fusion Networks(DAFFnet),which se...; 关键词：Soybean seed Classification Deep learning Neural networks Attention mechanisms

Graph distillation with network symmetry: 《Chinese Physics B》2025年第4期262-271,共10页Feng Lin Jia-Lin He; Project supported by the National Natural Science Foundation of China(Grant No.62176217);the Program from the Sichuan Provincial Science and Technology,China(Grant No.2018RZ0081);the Fundamental Research Funds of China West Normal University(Grant No.17E063).; Graph neural networks(GNNs)have demonstrated excellent performance in graph representation learning.However,as the volume of graph data grows,issues related to cost and efficiency become increasingly prominent.Graph d...; 关键词：graph neural networks graph distillation network symmetry super nodes feature optimization

A Survey of the Application of Neural Networks to Event Extraction: 《Tsinghua Science and Technology》2025年第2期748-768,共21页Jianye Xie Yulan Zhang Huaizhen Kou Xiaoran Zhao Zhikang Feng Lekang Song Weiyi Zhong; Event extraction is an important part of natural language information extraction,and it’s widely employed in other natural language processing tasks including question answering and machine reading comprehension.Howe...; 关键词：event extraction natural language processing event extraction methods graph neural network prompt-based learning

Causally enhanced initial conditions: A novel soft constraints strategy for physics informed neural networks: 《Chinese Physics B》2025年第4期365-375,共11页Wenshu Zha Dongsheng Chen Daolun Li Luhang Shen Enyuan Chen; supported by the National Natural Science Foundation of China(Grant Nos.1217211 and 12372244).; Physics informed neural networks(PINNs)are a deep learning approach designed to solve partial differential equations(PDEs).Accurately learning the initial conditions is crucial when employing PINNs to solve PDEs.Howev...; 关键词：initial condition physics informed neural networks temporal march causality coefficient

Digital Twin-Supported Battery State Estimation Based on TCN-LSTM Neural Networks and Transfer Learning: 《CSEE Journal of Power and Energy Systems》2025年第2期567-579,共13页Kai Zhao Ying Liu Yue Zhou Wenlong Ming Jianzhong Wu; Estimating battery states such as State of Charge(SOC)and State of Health(SOH)is an essential component in developing energy storage technologies,which require accurate estimation of complex and nonlinear systems.A si...; 关键词：Battery energy storage system battery state estimation deep learning digital twin transfer learning

Application of machine learning in astronomical spectral data mining: 《Astronomical Techniques and Instruments》2025年第2期73-87,共15页Ting Zhang Hailong Zhang Yazhou Zhang Xu Du Wenna Cai Han Wu Yuyue Jiao Wanqiong Wang Jie Wang Xinchen Ye Jia Li; supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502);the National Natural Science Foundation of China(NSFC)(12173077);the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112);the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01);China National Astronomical Data Center(NADC);the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences;Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).; Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectro...; 关键词：Machine learning Neural networks Stellar atmospheric parameter prediction Stellar spectral classification

Integrating Bayesian and Convolution Neural Network for Uncertainty Estimation of Cataract from Fundus Images: 《Computer Modeling in Engineering & Sciences》2025年第4期569-592,共24页Anandhavalli Muniasamy Ashwag Alasmari; Saudi Arabia for funding this work through Small Research Group Project under Grant Number RGP.1/316/45.; The effective and timely diagnosis and treatment of ocular diseases are key to the rapid recovery of patients.Today,the mass disease that needs attention in this context is cataracts.Although deep learning has signifi...; 关键词：Bayesian neural networks(BNNs) convolution neural networks(CNN) Bayesian convolution neural networks(BCNNs) predictive modeling precision medicine uncertainty quantification

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

NEURAL_NETWORKS

检索结果分析

下载全文

高级检索检索式检索

时间限定

期刊范围

学科限定全选

高级检索 检索式检索

时间限定

期刊范围

学科限定全选

NEURAL_NETWORKS

检索结果分析

下载全文

用户登录

高级检索检索式检索